A number of testing protocols have been established to diagnose speech quality degradation issues in communication systems. These testing protocols have been compiled by the International Telecommunication Union (ITU) into a number of standards. For example, two standards often used in diagnosing speech quality issues include ITU Standard P.861 and ITU Standard P.862. The speech quality tests prescribed in the above-mentioned standards require transmission of a voice pattern through a communication network and evaluation of the degradation within the voice pattern as received from the communication network.
Evaluation of the voice pattern degradation involves comparison of the degraded voice pattern with an undegraded version of the voice pattern. However, before the comparison can be made, the degraded and undegraded voice patterns need to be properly aligned. To facilitate this alignment in view of potential degradation within the received voice pattern, the standards recommend applying a cross-correlation function to the degraded and undegraded voice patterns to determine an amount of offset adjustment necessary to obtain the best alignment.
Application of the cross-correlation function to facilitate voice pattern alignment is expensive in terms of computational resources and time. Therefore, when performing speech quality testing on a number of channels within a communication network, performance of the cross-correlation function to align the voice patterns can become a bottleneck in the testing process.